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Full-Text Articles in Computer Engineering
Dynamic Modelling Of Dissolved Organic Carbon Concentrations In The Severn-Thames River Systems And Assessment Of The Impact Of A Water Transfer, Jaeyoung Lee, Gianbattista Bussi, Paul Whitehead, Martyn Futter, Jim Hall
Dynamic Modelling Of Dissolved Organic Carbon Concentrations In The Severn-Thames River Systems And Assessment Of The Impact Of A Water Transfer, Jaeyoung Lee, Gianbattista Bussi, Paul Whitehead, Martyn Futter, Jim Hall
International Congress on Environmental Modelling and Software
The aim of this modelling study has been to assess Dissolved Organic Carbon (DOC) in the River Thames and River Severn and the impacts of water transfers from in drought or low flow years. The transfer of water from the River Severn to the Thames is a water resource option under consideration by Thames Water as part of Water Resource Management Plan 2014. Rising trends of DOC in upland rivers in Wales have been observed over the past 15 years and with the proposed water transfer there is a chance that high DOC concentrations might be transferred across to the …
Towards A Neural Networks-Based Prediction Tool Devoted To Low Water-Levels Forecasting: Relevant Architecture Selection Based On Main Physical Processes, A. Coutouis, A. Johannet, S. Pistre, P. -A. Ayral, L. Cadilhac
Towards A Neural Networks-Based Prediction Tool Devoted To Low Water-Levels Forecasting: Relevant Architecture Selection Based On Main Physical Processes, A. Coutouis, A. Johannet, S. Pistre, P. -A. Ayral, L. Cadilhac
International Congress on Environmental Modelling and Software
Karst aquifers provide water resource for a large part of the Mediterranean population and water resource becomes a strategic problem during summer when population increases due to tourism. To help managers to optimize the exploitation of water, this work studies the ability of a neural network model to efficiently simulate water levels in the Cèze River, connected to a karst aquifer, few months ahead during the dry season. The neural model is based on recurrent multilayer perceptrons that learn the relations between inputs (mainly rainfall and ETP) and output (water level). After a training step using 17 years of data, …